We consider three SVAD algorithms: the unsupervised segment-based robust VAD (rVAD) by Tan et al. [1]}, [2]}; the ITU-T recommendation G.729 annex B voice encoder (G729B) [3]}; and the statistical model-based VAD (SOHN) by Sohn et al. [4]}.
The combination of the proposed pre-processing methods and SVAD algorithms is compared with a MVAD called frequency selective normalised difference power spectral density (FS-NDPSD) VAD by S. Hwang et al. [5]}.
To evaluate the proposed method acoustic environments are simulated.
The results show that all of the presented SVAD algorithms can be improved by the pre-processing methods.
Furthermore, for low signal-to-noise ratios SVAD with pre-processing outperforms the FS-NDPSD.
